ABSTRACT
Estimation of design floods is typically required for hydrologic design purpose. Design floods are routinely estimated for water resources planning, dam safety and risk analysis of the existing water-related structures. However, streamflow data for the design purposes in South Korea are still very limited, and additionally the length of streamflow data is relatively very short compared to the rainfall data. Therefore, this study collected a large number flood data (e.g. design flood, return period) and watershed characteristics (e.g. area and slope) from the national river database. Here, we revisited the Creager flood peak-drainage area relationship for the estimation of design flood using a quantile regression approach. More specifically, this study adopted a Hierarchical Bayesian model for evaluating both parameters and their uncertainties in the Creager model, which aims to evaluate the hydrologic response of ungauged basins in the context of regression framework. The proposed modeling framework was validated through gauged watersheds within a cross-validation scheme. The model showed better performance in terms of correlation coefficient than the existing approach which is solely based on area as a predictor under an ordinary regression approach. Moreover, the proposed approach can provide uncertainty associated with the model parameters to better characterize design floods at ungauged watersheds
